Overcoming AI Deployment Challenges in Banking GRC
When the AI Worked Fine. We Were the Problem. There is a version of the AI-in-banking story that gets told at conferences. The version with the elegant architecture diagram, the impressive accuracy metrics, the CTO on stage explaining how they transformed their compliance operations in eighteen months. Applause. Networking drinks. Everyone flies home feeling slightly inadequate. Then there is the version I lived. In 2022, I was part of a team running AI pilots across GRC functions inside a large bank. Six pilots. Reasonable budget. Good vendor relationships. Genuine executive appetite – the rare kind where people actually showed up to the steering committee rather than sending a delegate to take notes. By every measure that matters before you start, we had the conditions for success. Every single pilot stalled at the same wall. — The Wall Nobody Puts in the Business Case The wall was not the technology. I want to be clear about that, because the easy narrative – the one that protects everyone’s prior decisions – is to blame the vendor, blame the model, blame AI for not being ready. That narrative is comfortable and wrong. The wall was our data. Specifically, the state of it. Which is to say: the state of twenty years of accumulated decisions, mergers, system migrations, and the quiet institutional habit of solving urgent problems without fixing underlying ones. Here is the moment I remember most clearly. We had a transaction monitoring model that was genuinely impressive in the sandbox. Clean inputs, clean outputs, the kind of performance that makes a proof-of-concept presentation feel like a TED talk. We moved it toward live deployment and ran the first serious data profiling exercise against our actual production environment. Our data taxonomy contained seventeen different definitions of “beneficial owner” across legacy systems. Seventeen. The model was not confused. The model was doing exactly what models do – processing the inputs it received according to the logic it had learned. We were confused. We had built seventeen slightly different answers to the same regulatory question, across different systems, over different years, and we had simply never needed to look at them all in the same room before. AI did not create that problem. It just turned on the lights. I spent approximately forty-eight hours after that discovery in a state that I can only describe as professionally humbling. I had been in regulated financial services long enough to know that data quality was important. I had said the words “data governance” in enough board papers to have strong opinions about font size. And yet here I was, learning that my organisation did not have a consistent answer to a question that regulators had been asking for years. The AI pilot did not fail. It diagnosed. — What the POC Was Actually Testing The proof-of-concept works because you give it clean, curated data. That is not a criticism of how pilots are designed – it is simply what they are. You select a representative sample, you prepare it, you load it, and you measure performance against a problem you have defined carefully. The POC answers the question: can this technology do what we hope, given the right conditions? That is a useful question. It is not the question that matters. The question that matters is: what are the actual conditions inside this organisation? And the answer to that question, in most large banks I have worked with or alongside, is some variation of: complicated, undocumented, and older than the team currently responsible for it. The gap between sandbox and production is not a technical gap. It is a data archaeology gap. This is the insight that took me too long to reach, and I say that as someone who had read enough about data quality to have formed opinions about it. Knowing that data quality matters is not the same as knowing what it looks like when your specific data estate is the problem. Those are different kinds of knowing, and only one of them is available before you start the work. — Why Transformation Announcements Age Badly There is a related pattern I have observed across organisations – and I wrote about something adjacent to this when reflecting on regulatory conversations in Toronto around crypto adoption, where the same dynamic appears in a different form: the gap between announcing transformation and executing it tends to open exactly at the point where unglamorous remediation work needs to happen and nobody wants to own it. AI deployment in regulated banking is not primarily a technology programme. It is a data remediation programme with a model at the end of it. The model is, in some ways, the reward for doing the hard work – not the hard work itself. The six months of data taxonomy reconciliation, legacy system mapping, beneficial ownership standardisation, and governance framework alignment that has to precede meaningful AI deployment: that work does not make it into the press release. It does not generate a conference talk. It does not produce a metric that looks good in a board update. It produces the conditions under which the actual work becomes possible. Senior leaders who understand this – and I have met perhaps a handful who genuinely do – structure their AI programmes accordingly. They do not budget for a pilot and a deployment. They budget for a data programme, a remediation phase, a governance layer, and then, eventually, a model. The timeline feels slower. It also actually works. The connection to cyber risk is worth naming too: as I explored in a previous piece on the human side of cyber risk, the most dangerous vulnerabilities in complex organisations are rarely the ones the technology missed. They are the ones the organisation had quietly decided not to look at. Data debt in AI deployment has the same character. — What This Means If You Are Planning the Next Pilot If you are a risk, compliance, or technology leader in a regulated institution and you
Crypto Regulation in Banking: Leadership Lessons Learned
Crypto Regulation Has Arrived. The Gap Between Policy and Plumbing Is Where Institutions Will Fail. — There is a particular quality to conversations that happen when senior people stop performing and start problem-solving. You can feel the room shift. The language changes. The careful corporate phrasing gives way to something more honest. That is what happened in Toronto last week – and what came out of it is worth documenting properly. I was in a room with banking and fintech leaders working through what the new crypto regulatory framework actually means in practice. Not in theory. Not in a panel discussion designed for an audience. In practice, with people who are responsible for making this work inside real organisations with legacy systems, constrained budgets, and boards who are still not entirely sure what a blockchain is. The conversation confirmed something I have suspected for months. Crypto regulation is no longer approaching. It has arrived. And the industry is discovering, in real time, that being ready in principle is not the same as being ready in operation. — The Room in Toronto The meeting was not a conference. It was a working session – the kind where the agenda has substance and the attendees have skin in the game. Compliance heads. Risk directors. Fintech founders. A few people from the banking side who have been quietly building crypto infrastructure while their public communications remained carefully neutral on the subject. What struck me within the first hour was how consistent the problem was, regardless of the size of the institution or the sophistication of the team. Every organisation in that room had a version of the same challenge. The regulatory expectation was documented. The internal policy existed. The gap was in execution – in the systems, workflows, controls, and data infrastructure that have to translate policy language into daily operational reality. One senior leader said it plainly, without any visible embarrassment: “We have the policy. We don’t have the plumbing.” That sentence has stayed with me. It is the most honest diagnosis of the current implementation crisis I have heard. And it was not said by someone who had been slow or negligent. It was said by someone who had done the right things – engaged legal counsel, built the governance framework, briefed the board – and was now staring at the distance between where their documentation said they were and where their operations actually were. That distance is where the real regulatory risk lives. — Three Things This Told Me First: the speed mismatch is structural, and most organisations have not accounted for it. Regulation moves at the speed of legislation and political will. Operational infrastructure moves at the speed of procurement cycles, vendor negotiations, integration timelines, and internal change management. These are not comparable speeds. Regulatory frameworks for crypto are evolving in months. Core banking systems that need to interface with those frameworks were built over years and are modified in quarters. I have watched this exact dynamic play out before. In AML reform in the late 2010s. In the GDPR rollout. In MiFID II. In each case, the organisations that suffered most were not the ones that disagreed with the regulation – they were the ones that treated the legislative calendar as their operational deadline. They waited for final text. Then they scoped. Then they procured. Then they discovered that the implementation timeline they needed was longer than the compliance deadline they had. Crypto is going to catch a significant number of institutions in exactly this trap. Second: the gap between sophisticated language and operational readiness is wider than most senior teams realise. One of the more uncomfortable dynamics in that Toronto room was the contrast between how fluently people could discuss the regulatory framework and how candidly they acknowledged their execution challenges once the conversation moved past the formal agenda. The policy language, the governance structures, the board presentations – these were polished. The underlying question of whether the transaction monitoring systems could actually flag the activity the regulation required them to flag – that was a different conversation entirely. This is not a criticism of the people in that room. Most of them were operating with significant constraints: technology debt, budget cycles that predate the regulatory shift, and the particular difficulty of explaining infrastructure spend to a board that views crypto compliance as a niche problem rather than a systemic risk. But it is a warning about the gap between what organisations say in regulatory submissions and what their systems can actually execute. That gap is not sustainable. And regulators – particularly as enforcement moves from guidance to action – will find it. Third: the organisations that will lead are already building, despite the uncertainty. This is the pattern I have seen in every major regulatory transition of the past two decades. The winners are not the ones with the most sophisticated legal interpretation. They are the ones who started building operational capability before the rules were final – and who accepted, from the start, that some of what they built would need to be adjusted. This requires a particular kind of institutional nerve. There is always a voice in the room that says: wait for certainty. Do not over-invest in an interpretation that may shift. The voice is not wrong on the logic. But it consistently underestimates the cost of starting late. Waiting for certainty is not a neutral position. It is a choice with consequences – and in regulatory implementation, those consequences typically compound. — What This Means for Your Organisation If you are in a leadership role – compliance, risk, technology, or executive – in any institution with material crypto exposure or ambition, the question is not whether to act. The question is whether the gap between your policy documentation and your operational infrastructure is visible to you before it becomes visible to a regulator or a failure event. The diagnostic is straightforward, even if the answer is not. Can your current systems
Behavioral Risk, The Quiet Threat No One Sees Coming
Behavioral Risk – The Quiet Threat No One Sees Coming A Perfect Audit. A Flawed Culture. Not long ago, I walked into a senior management meeting at a well-respected institution where everything looked perfect on paper. Their compliance checklist was pristine. Their risk controls ticked every box. The auditors had just given them a clean bill of health. Yet, within three months, the firm found itself on the front page – embroiled in a scandal involving rogue trading and falsified client reports. What failed? Not the systems. Not the documentation. Culture failed. Behavior failed. This wasn’t a technology gap or a policy oversight. This was behavioral risk – the threat posed by human decisions, incentives, blind spots, and silence. And it’s the most underestimated risk in modern finance. What Exactly Is Behavioral Risk? Behavioral risk refers to the risk of misconduct, poor judgment, or unethical decision-making by employees – even in the absence of malicious intent. It’s not always about bad actors. Sometimes it’s good people making poor choices under pressure, fear, or misaligned incentives. Remember Wells Fargo’s 2016 scandal? Thousands of fake accounts were opened, not by fraudsters, but by employees chasing unrealistic sales goals. The incentive structure was flawed, oversight was lax, and a toxic “deliver-at-all-costs” culture turned good intentions into bad behavior. That’s behavioral risk at work. Story: The Silence That Cost Millions In one of my early transformation projects, we introduced a new control framework. It looked solid on the surface. But something didn’t feel right. The team seemed tense. When I asked if there were concerns, most stayed quiet. Until one brave junior analyst pulled me aside. “Honestly,” she whispered, “we’re skipping the validation steps. Management says they’re too time-consuming and wants us to just sign off.” We were missing a behavioral breakdown in real time – pressure to deliver > process integrity. We paused, investigated quietly, and confirmed it. No fraud, no ill will – just a culture of fear, silence, and impossible deadlines. We revamped not just the process, but the environment. We held listening sessions, adjusted KPIs, and introduced an anonymous feedback mechanism tied to our risk dashboards. That’s how you fix behavioral risk: you make people feel safe to speak. Why Traditional Controls Miss the Mark You can’t mitigate behavioral risk with policies alone. People don’t read policies when they’re overwhelmed. And they don’t report misconduct when they think their job is on the line. Tone at the top matters. But echo in the middle matters more. Middle managers shape day-to-day behavior more than any CEO ever could. If they reward speed over accuracy, or silence over escalation, risk thrives in the gaps. According to the Harvard Business Review, organizations that embed psychological safety are 27% more likely to detect early warning signs of misconduct. That’s not just good ethics – it’s smart risk management. Behavioral Risk Meets AI and Surveillance Many firms now use AI to detect potential behavioral red flags: Email sentiment analysis Voice tone detection in call centers Chat logs scanned for insider trading signals That’s powerful – but it’s not enough. You can’t fix culture with algorithms alone. AI may flag the symptom, but it’s leadership that must cure the cause. The Role of Training – and Its Limits Many institutions rely on mandatory training to combat misconduct. But if training is boring, disconnected from real-life pressures, or seen as a chore, it’s ignored. The most effective behavioral risk programs I’ve seen? Use interactive scenario-based training Tie real-world events to personal accountability Involve leadership in live discussions, not just e-learning modules You need hearts and minds, not just compliance clicks. Behavioral Risk = Reputational Risk Remember: it only takes one incident to damage trust. Ask Boeing. Ask Credit Suisse. Ask any firm whose internal behavior became external headlines. Behavioral risk isn’t just an internal matter – it directly impacts reputation, shareholder confidence, and regulatory scrutiny. Final Thought: Culture is the Ultimate Control You can’t fully automate human integrity. That’s why leaders need to do more than monitor. We must model. We must ask uncomfortable questions. And we must build environments where doing the right thing isn’t just safe – it’s celebrated. Because in the end, the most dangerous risks are the ones we’re too afraid to talk about. About the Author Laksh Vaswani is a financial services executive, award-winning author, and global transformation leader specializing in risk, compliance, and regulatory governance. With over two decades of experience, he has guided financial institutions through operational crises, regulatory exams, and cultural transformations. Laksh is a recipient of the International Achievers Award and a vocal advocate for ethical leadership and behavioral resilience. Share this article :
Final Reflections from the Front Lines of Finance
Final Reflections from the Front Lines of Finance The first time I truly understood risk, it wasn’t from a textbook. It was early in my career. I was shadowing a senior executive at a global bank when a rogue trading incident hit the front pages. Overnight, billions vanished. The mood in the office shifted from confident to cautious. You could feel the air tighten. I asked him quietly, “What happened?” He didn’t say much. Just looked up and said, “Someone somewhere believed it wouldn’t happen here.” That one line stuck with me. Because that’s how risk works – quietly, invisibly, and then suddenly, all at once. We All Work in Risk. Whether We Know It or Not. Over the course of this series, we’ve talked about operational risk, reputational damage, innovation, compliance, audits, MRAs and MRIAs, regulatory exams, even moments of crisis when resilience is tested on train tracks – literally. But here’s the truth behind all of it: Risk isn’t a department. It’s a mindset. It’s in every decision we make – from the new product we launch to the shortcut we consider, to the silence we allow in meetings when we should have spoken up. And if there’s anything I’ve learned in 20+ years navigating the world of financial governance and transformation, it’s that the most dangerous risk is the one we think we’ve already covered. Lessons in Humility (and Humor) Let’s be honest – no one wakes up excited to do a Risk Control Self-Assessment. No one dreams of drafting a Volcker Rule attestation. And when a regulator says “we’d like to discuss your resolution planning framework,” your heart doesn’t leap with joy. But these aren’t just check-the-box exercises. They’re stories. They’re scars. They’re proof that we’ve tried, failed, improved, and evolved. Like the time we submitted a 400-page RCSA and forgot to include cyber risk. Or when a junior analyst flagged an unencrypted server and saved us from a headline we never want to read. Or the time we got it all right on paper – only to fail the cultural test that no audit could catch. Risk, at its core, is human. And so the solutions have to be human too. Courage, Not Control, Is What Makes Great Risk Leaders In every story we’ve explored, from managing operational resilience to navigating innovation with regulators breathing down our necks, the leaders who stood out weren’t the ones who played it safest. They were the ones who were honest about uncertainty. They created space for hard questions. They told their teams, “I don’t know either – let’s figure it out together.”They resisted the urge to sanitize risk reports and instead exposed the real issues, even if it meant a tougher conversation with senior management. They understood that risk is not just something to “manage” – it’s something to lead through. So, What Do We Do Now? If you’ve read this far, you’re probably someone who takes governance seriously. Someone who knows that trust is built over time – and lost in seconds. So here’s what I’ll leave you with: If you’re building risk frameworks, build them with curiosity, not just compliance. If you’re leading through uncertainty, prioritize clarity over perfection. And if you’re mentoring others, teach them that risk isn’t something to fear – it’s a lens for better decisions. Because at the end of the day, whether you’re a risk officer, a CEO, a product lead, or a startup founder – you’re in the business of decision-making under uncertainty. That’s all risk really is. And that’s what makes it powerful. About the Author Laksh Vaswani is a global financial executive, transformation strategist, and best-selling author with more than two decades of experience helping organizations navigate complex risk landscapes. A mentor, thought leader, and recipient of the International Achievers Award, Laksh has led risk and compliance efforts at major global institutions across the U.S., Europe, and Asia. Through The Risk Chronicles, he shares lessons from the trenches – not to preach, but to invite others into the ongoing conversation of building better, stronger, more ethical organizations. Share this article :
When Firewalls Fail, The Human Side of Cyber Risk
When Firewalls Fail – The Human Side of Cyber Risk The Wake-Up Call That Came at 3:12 AM A few years ago, I received a call no operations executive ever wants to get.“Laksh, we’ve had a breach.”That was it. Six words. But behind them were two thousand frozen screens, a ransomware note, and one innocent click from a colleague trying to download a “secure attachment” from what appeared to be a trusted vendor. As much as we had trained staff and layered our tech stack with the latest SIEM tools and threat detection software, the reality hit hard: Cyber risk is not just an IT problem – it’s a business resilience problem. Lesson 1: People Are the First – and Weakest – Firewall We had invested millions in cybersecurity. And yet, our breach came not from some sophisticated zero-day exploit, but from someone clicking a phishing link sent during peak business hours. It reminded me of the famous quote by Bruce Schneier: “Amateurs hack systems, professionals hack people.” We had overlooked something simple – our people were overwhelmed with alerts and compliance training fatigue. We needed engagement, not just education. So, we rolled out gamified phishing simulations, lunch-and-learns with real cyber stories, and even made password reset day a mini-office event. Outcome? Click rates dropped. Awareness rose. People were no longer passive gatekeepers – they became active defenders. Lesson 2: Not All Data Is Created Equal Post-breach, we conducted a data prioritization audit. Turns out, we were “protecting” some files like nuclear codes… and leaving truly sensitive ones less guarded. Here’s the thing about data: volume ≠ value. So, we redesigned our controls using data classification frameworks like those recommended by NIST and ISO/IEC 27001. Critical data was encrypted, monitored, and access-controlled. Non-sensitive material was moved to less critical environments – less complexity, less exposure. Lesson 3: You Can’t Outsource Accountability Many of us trust our vendors with our most sensitive data – from payroll processors to cloud providers. But cyber risk doesn’t vanish when you outsource it. In fact, third-party vendors account for over 60% of data breaches, according to a Ponemon Institute study. We learned this firsthand when one of our cloud vendors suffered a breach. They were compliant – but their subcontractor wasn’t.We had to answer for it. So, we built a Third-Party Cyber Risk Framework that went beyond just reviewing SOC reports. We conducted due diligence, required evidence of multi-factor authentication (MFA), and introduced breach notification SLAs. Trust, but verify. Then verify again. Lesson 4: Don’t Just React – Rehearse Back to that 3:12 AM call. One silver lining? We had rehearsed this exact scenario during our Business Continuity & Incident Response tabletop exercises.Because of that, teams knew their roles. Legal drafted statements, PR was briefed, IT isolated servers, and clients were proactively informed before the headlines hit. We discovered that what mattered most was not just how we recovered, but how transparently and swiftly we communicated. Looking Ahead: Cyber Risk Is a Moving Target The cyber threat landscape is evolving – AI-powered attacks, deepfakes, nation-state hackers. You can’t eliminate cyber risk, but you can build cyber resilience. Resilience isn’t about having the best tech. It’s about: Creating a culture of awareness Investing in real-time detection and response Practicing recovery before you need it Embedding cyber strategy into boardroom conversations, not just IT updates As regulators like NYDFS, OCC, and SEC tighten cybersecurity standards, leaders must rise beyond compliance checklists and build organizations that are agile, secure, and responsive. About the Author Laksh Vaswani is a global financial services executive, best-selling author, and recipient of the International Achievers Award. With over two decades of experience in regulatory transformation, risk governance, and operational resilience, he has helped institutions navigate complex cyber threats and regulatory expectations across North America, EMEA, and Asia. Laksh is a passionate mentor, speaker, and thought leader in financial innovation and risk management. Share this article :
When Partners Become Liabilities, Rethinking Third-Party Risk
When Partners Become Liabilities – Rethinking Third-Party Risk The Day a Payroll Vendor Brought Us to a Halt It was a routine Friday morning – until it wasn’t. Phones lit up. Systems slowed down. HR couldn’t run payroll. Finance couldn’t close the books. Our third-party payroll vendor had gone offline, caught in the crossfire of a ransomware attack that had nothing to do with us… or so we thought. But regulators didn’t see it that way. To them, it was our responsibility. And they were right. We had outsourced the service, not the risk. Why Third-Party Risk Is Everyone’s Risk Today, financial institutions rely on a complex web of vendors: fintech partners, cloud providers, legal consultants, data processors, offshore support teams – and the list keeps growing. Each one is a node in your ecosystem. Each one can be a vector for operational, reputational, or cyber risk. According to Deloitte, 83% of organizations have experienced a third-party incident in the past three years. And yet, fewer than half conduct deep risk assessments beyond onboarding. That’s not a strategy. That’s a gamble. Lesson 1: More Than a Box to Check I once worked with a firm where vendor risk assessments were essentially a tick-the-box process. “Do they have a SOC 2 report?”“Yes.”“Great, move on.” No one read it. No one asked what systems were in scope. No one noticed the outdated controls in their user access reviews. It wasn’t until a regulator showed up – asking very specific questions about sub-service organizations and data segregation – that the panic set in. We had assumed compliance. We hadn’t verified capability. The fix? We revamped the Third-Party Risk Management (TPRM) lifecycle: Replaced checkbox reviews with risk-tiered due diligence Added on-site assessments for critical vendors Integrated real-time monitoring for ongoing risk awareness The idea wasn’t to make life harder – it was to make it smarter. Lesson 2: Subcontractors Are Still Your Risk Here’s the kicker: the payroll vendor that caused our outage?They weren’t breached. Their subcontractor was. We didn’t even know about the subcontractor. That’s why the OCC’s Third-Party Risk Management Guidelines emphasize “chain-of-responsibility.” If your vendor relies on someone else, you still own the exposure. Now, all our contracts include: Disclosure of all subcontractors Right-to-audit clauses Breach notification timeframes Incident response collaboration expectations It’s not about micromanaging. It’s about governance. Lesson 3: Risk Never Ends at Onboarding Vendor due diligence isn’t a one-and-done task. One of our cloud providers was financially stable when we onboarded them. Two years later, their parent company was in bankruptcy court. Our access was nearly compromised. From that day forward, we implemented ongoing risk monitoring using platforms like: BitSight (for cyber hygiene scoring) ProcessUnity (for TPRM workflow management) LexisNexis (for legal and reputational red flags) Vendor relationships evolve. So must your oversight. Lesson 4: Culture Still Matters Here’s something we often forget: third-party vendors are people too. When the pandemic hit, one of our offshore support vendors struggled with lockdowns and limited internet access. It wasn’t their fault. But we hadn’t planned for it. That’s when we shifted from thinking of vendors as contracts to thinking of them as strategic partners. We began: Hosting joint resilience workshops Aligning KPIs on client outcomes, not just deliverables Sharing incident response plans and testing together Resilience is a team sport. Final Thought: The Chain is Only as Strong as Its Quietest Link Third-party risk isn’t just a function. It’s a philosophy. It’s about asking the hard questions before a regulator does.It’s about looking beyond the glossy onboarding decks and into the operational realities.And above all, it’s about remembering that outsourcing the work doesn’t mean outsourcing the responsibility. About the Author Laksh Vaswani is a senior financial executive, best-selling author, and global risk governance strategist. With over two decades of experience leading transformation, regulatory readiness, and vendor risk management programs across banking and fintech, he has helped organizations balance innovation with resilience. Laksh is the recipient of the International Achievers Award and an advocate for smarter, human-centric compliance. Share this article :
U.S. vs Europe: Navigating Regulatory Expectations Across Borders
single post U.S. vs Europe: Navigating Regulatory Expectations Across Borders The global financial ecosystem is increasingly interconnected, but the regulatory frameworks that govern it often aren’t. When firms operate across both U.S. and European markets, the challenge becomes less about the rules themselves and more about the differences in approach, enforcement, and interpretation. Having consulted with organizations navigating both worlds, I’ve come to appreciate how nuanced cross-border compliance can be – and how it can be turned into a competitive advantage when handled thoughtfully. Let’s start with what they have in common. Both the U.S. and Europe demand rigorous controls around risk management, data privacy, anti-money laundering (AML), and operational resilience. But the way these themes are implemented and enforced can vary dramatically. 1. Regulatory Philosophy: Rules-Based vs Principles-Based In the U.S., regulatory agencies like the Office of the Comptroller of the Currency (OCC), Federal Reserve Board (FRB), and Securities and Exchange Commission (SEC) adopt a rules-based approach. Regulations are specific, and deviations come with clearly defined penalties. Contrast this with Europe, where regulators like the European Central Bank (ECB) and Financial Conduct Authority (FCA) operate on a principles-based model. Under frameworks like MiFID II and CRD IV, firms are expected to meet broad outcomes, but how they do so is left to interpretation. Lesson: In one engagement, I advised a Caribbean bank expanding into Europe. They were used to U.S.-style playbooks and sought detailed checklists. But in London, they had to adapt – demonstrating how their controls aligned with the Senior Managers and Certification Regime (SMCR) and FCA’s Treating Customers Fairly principles. We built governance dashboards using ServiceNow GRC to map control effectiveness to regulatory outcomes, providing the transparency the FCA valued. 2. Data Privacy: GDPR vs U.S. Patchwork In Europe, data privacy is governed by General Data Protection Regulation (GDPR), a sweeping regulation that applies across EU member states. In contrast, the U.S. has a fragmented framework, with laws like CCPA (California), GLBA, and HIPAA applying based on jurisdiction and industry. Lesson: A U.S.-based fintech client of mine, with operations in Paris and Berlin, had to completely revamp their customer onboarding workflows. We implemented OneTrust for consent tracking and automated Subject Access Requests (SARs) using Salesforce Service Cloud, reducing risk and increasing customer trust. 3. Anti-Money Laundering (AML): Scope and Reporting Both regimes require strong AML programs, but the enforcement is more aggressive in the U.S., particularly under FinCEN and the Bank Secrecy Act (BSA). Europe aligns through 4AMLD and 5AMLD, but reporting thresholds and enforcement rigor can differ. Lesson: While consulting for a bank operating under both regimes, we used Actimize AML to streamline transaction monitoring and SAS AML for intelligent alert prioritization. We adjusted rulesets regionally and created a crosswalk between Suspicious Activity Report (SAR) requirements in the U.S. and STRs in the EU. 4. Operational Resilience and Recovery Planning U.S. regulators now expect banks to integrate Operational Resilience into their Recovery & Resolution Planning (RRP) processes – especially under OCC Bulletin 2019-64 and FRB expectations. Europe mandates resilience under DORA (Digital Operational Resilience Act) and EBA Guidelines on ICT and security risk. Lesson: At a prior institution, we centralized BCP and resilience planning across regions using Fusion Framework System. It helped standardize risk appetite statements, impact tolerance thresholds, and crisis playbooks. This not only ensured compliance but created a proactive resilience culture across both jurisdictions. 5. Best Practices: Bridging the Divide Here’s what we’ve learned from working on both sides of the pond: Harmonize Where You Can: Use tools like MetricStream, Archer, or LogicManager to unify risk taxonomies and reporting standards. Customize Where You Must: Accept that some requirements can’t be harmonized. Build region-specific controls where needed. Invest in RegTech: Automate regulatory horizon scanning with tools like Thomson Reuters Regulatory Intelligence or Wolters Kluwer OneSumX. Cultural Adaptability Matters: The success of any framework lies in how well it’s embraced. Train teams on both U.S. and EU expectations, not just the rules but the “why” behind them. Final Thoughts Navigating regulatory expectations across U.S. and European borders isn’t about choosing sides – it’s about understanding both. The best firms use these differences as opportunities to elevate their governance, sharpen their risk posture, and foster international credibility. And if you’re still building those bridges? Don’t worry. We all start somewhere. About the Author Laksh Vaswani is a global financial services executive and regulatory advisor who has helped institutions navigate complex regulatory environments across the U.S., Europe, and the Caribbean. A best-selling author and International Achievers Award winner, Laksh specializes in operational transformation, risk governance, and cross-border compliance. Connect with him on LinkedIn or visit www.lakshvaswani.com for insights and advisory services. Share this article :
When the System Blinks: Understanding and Managing Technology Risk in Financial Services
When the System Blinks: Understanding and Managing Technology Risk in Financial Services One late afternoon, in a well-known financial services firm, a routine end-of-day batch job failed to kick off. A simple scheduling error, it seemed. But that single misfire led to an overnight reconciliation backlog, delayed settlements, and an early morning call with a regulator who’d noticed the delayed reporting. That was the moment we learned: in today’s digitized financial landscape, technology risk isn’t just a back-office concern – it’s front-page news waiting to happen. Technology risk refers to the potential for losses stemming from the failure of systems, software, networks, or third-party tech services. It may be triggered by outdated infrastructure, coding errors, cyberattacks, third-party failures, or even well-meaning automation that no one quite tested properly. The consequences? Reputational damage, financial loss, and regulatory scrutiny. The Chain Reaction Nobody Wants Several years ago, I worked with a global asset manager undergoing a cloud migration. It sounded exciting. The cost savings and scalability benefits were all there. But what wasn’t on the slide deck was how many business-critical applications still depended on legacy architecture that wasn’t cloud-compatible. In one instance, a reporting tool that pulled position data for risk oversight failed to retrieve accurate feeds after the cloud switchover. The result? Inaccurate risk reports sent to internal committees and a scramble to recall and correct them before external eyes got involved. What did we learn? The importance of technology change governance. Before any major tech overhaul, every upstream and downstream dependency needs to be mapped, tested, and retested. Simple rule: if it can break, it probably will – unless you’ve planned for it not to. Cyber Risk: The Ever-Present Shadow No article on tech risk is complete without mentioning cybersecurity. And it isn’t just about firewalls and encryption. A breach can come from an innocuous email attachment. At another institution I advised, a phishing email compromised an employee’s credentials. No big deal, right? Wrong. The compromised ID had access to a dormant third-party file transfer protocol (FTP) server still linked to live customer data. That one oversight turned into a multi-month breach investigation. We took action quickly: reviewed all privileged access, killed off dormant accounts, revamped endpoint monitoring, and launched mandatory cyber-awareness training. But we also rewrote our third-party risk policy to emphasize identity lifecycle management and data minimization. Regulations and Frameworks: A Compass, Not a Crutch Regulators have taken note. The NYDFS Cybersecurity Regulation (23 NYCRR 500), GDPR, and FFIEC guidance all outline expectations for managing tech risk. Yet compliance with these laws shouldn’t be the ceiling – it should be the floor. One client of mine adopted the NIST Cybersecurity Framework as a strategic blueprint. By pairing it with FAIR (Factor Analysis of Information Risk) modeling, we quantified risk exposure in dollar terms. This helped the board better understand why we needed a budget increase for endpoint detection and response. Dollars and metrics speak louder than fear. The People Side of Technology Risk Technology risk is never just about the tech. People build, maintain, and use systems. And people are fallible. At a mid-sized bank, a developer wrote a script that bypassed a manual review step to speed up processing. It worked. Until one day, it didn’t. The script ingested corrupted data, which went unchecked, leading to a cascade of reconciliation issues across six business lines. It took days to untangle. This incident led to our “Human Factors in Technology Risk” initiative. We didn’t just audit the code. We started asking: Why did the developer feel the need to create a workaround? Was it a culture that celebrated speed over controls? Were teams empowered to report fragilities? These are cultural questions as much as operational ones. What Financial Institutions Must Do Map Dependencies – Understand how your systems connect, where the single points of failure lie, and who is accountable for each. Simulate Failure – Run tabletop exercises. Pull the plug (figuratively) on a major system and see what happens. Be surprised in a safe setting. Invest in Culture – Tech awareness, ownership of controls, and a psychologically safe environment to report issues are just as vital as tools and policies. Benchmark to Frameworks – Use NIST, COBIT, ISO 27001, or FFIEC not just for compliance but to drive maturity. Vendor Vigilance – Third-party risk is first-party risk in disguise. Have your vendors been tested? Audited? What’s their incident response time? About the Author Laksh Vaswani is a senior financial services executive and technology risk advisor with over 20 years of experience guiding institutions through digital transformation, regulatory compliance, and operational resilience. A best-selling author and International Achievers Award recipient, he is passionate about building governance frameworks that don’t just satisfy regulators, but make institutions stronger, safer, and smarter. Share this article :
The Silent Saboteur: Navigating Reputational Risk in Financial Services
The Silent Saboteur: Navigating Reputational Risk in Financial Services There are breaches that hit the front page, and then there are whispers that spread like wildfire. In the world of financial services, reputational risk is the kind that doesn’t knock – it slips quietly through the cracks, often catching even the most vigilant firms off guard. And unlike credit or market risk, it doesn’t show up neatly on a balance sheet. It lingers, shadows performance, and – if left unchecked – erodes trust at the core. I learned this the hard way. The Ripple Effect of a Client Misstep Several years ago, I was working with a bank that had a solid operational backbone, robust compliance program, and a stellar record with regulators. On paper, it was nearly flawless. But all it took was one client. A well-known fund that had questionable practices in a foreign jurisdiction made headlines for the wrong reasons. Although our firm had conducted standard due diligence, the association alone triggered media speculation, investor anxiety, and internal confusion. What stung the most wasn’t the direct financial impact – it was the reputational fallout. Clients began asking questions, business leads started slowing down, and internally, there was a surge of second-guessing across departments. It didn’t matter that we hadn’t done anything wrong. Perception had already taken hold. Reputation is the Shadow of All Other Risks Reputational risk rarely appears in isolation. It’s the consequence of other risks – compliance failures, cybersecurity breaches, poor leadership decisions, or even third-party blunders. It’s why we can’t treat it as a PR issue alone. It’s a risk category that needs its own governance, its own escalation protocol, and above all, a cross-functional ownership model. The challenge? Reputational risk often emerges from decisions that seem completely logical at the time. Launching a new product too quickly. Partnering with a fintech firm that hasn’t scaled its controls. Hiring a high-profile executive with skeletons in their closet. The market doesn’t wait for your side of the story – it runs with what it knows. Building a Proactive Reputational Risk Framework In one of the firms I worked with, we embedded reputational risk considerations into our product approval process. Every major initiative – whether it was a new market launch or a vendor partnership – had to go through a reputational risk lens. This wasn’t just about legal sign-off or compliance checklists. It involved risk officers, communications teams, and senior leadership asking the hard questions: What could go wrong, and how would that be perceived? Who are we partnering with, and what is their public history? How do we prepare for an external narrative that’s out of our control? We also created a “Reputation Risk Radar” – a real-time dashboard tracking social media sentiment, legal escalations, regulatory changes, and client behavior trends. The goal wasn’t to eliminate noise, but to detect early patterns. Transparency is Your Best Armor When a reputational issue does arise – and it will – it’s tempting to go quiet. Wait it out. Minimize exposure. But experience has taught me that transparency builds far more credibility than silence. We had an incident where sensitive client data was mistakenly shared – not a breach, just human error. Instead of burying the incident, we reached out directly to the affected clients, explained what happened, and detailed the corrective actions we were taking. Not only did we retain their trust, but in several cases, clients thanked us for the honesty. About the Author Laksh Vaswani is a senior financial services executive, mentor, and best-selling author who has spent over two decades leading governance, risk, and compliance transformations across global banks and financial institutions. His leadership has helped organizations navigate complex regulatory environments while preserving stakeholder trust and brand reputation. Share this article :